We conduct extensive experiments on CIFAR-10/100. Our results show that the proposed Attentive CutMix consistently improves the accuracy across a variety of popular network architectures (ResNet [1]}, DenseNet [2]} and EfficientNet [3]}). For instance, on CIFAR-100, we achieve 75.37% accurcy with ResNet-152, which is 2.16% higher than the baseline CutMix (73.21%).
